|Academic Profile |
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Assoc Prof Erik Cambria
School of Computer Science and Engineering
College of Engineering
Phone: (+65)6790 4328
- PhD (Computer Sci & Maths) University of Stirling 2012
- MEng (Elect Engrg) University of Genoa 2008
- BEng (Elect Engrg) University of Genoa 2005
|Erik Cambria is the Founder of SenticNet, a Singapore-based company offering B2B sentiment analysis services, and an Associate Professor at Nanyang Technological University, where he teaches and researches about AI and NLP. Prior to joining NTU, he worked at Microsoft Research Asia and HP Labs India and earned his PhD through a joint programme between the University of Stirling and MIT Media Lab. |
Erik is recipient of many awards, e.g., the 2018 AI's 10 to Watch and the 2019 IEEE Outstanding Early Career award, and is often featured in the news, e.g., Forbes. He is Associate Editor of several journals, e.g., NEUCOM, INFFUS, KBS, IEEE CIM and IEEE Intelligent Systems (where he manages the Department of Affective Computing and Sentiment Analysis), and is involved in many international conferences as program chair, PC member, workshop organizer, and invited speaker.
natural language understanding
- Big Social Data Analysis
- Brain-Inspired Natural Language Processing for the Time-Evolving Analysis of the Singaporean Blogosphere
- Gift funds - in support of research activities
- Human-Robot Collaborative AI for Advanced Manufacturing and Engineering (AME) Programmatic Grant : Commonsense Reasoning
- MICE - A Multilingual Corpus of Emotion Expressions of Malay, Indonesian, Chinese and English
- Maritime Silk Road. Past, Present and Future. A projection mapping concept design project
- PONdER: Public Opinion of Nuclear Energy
- Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis
- Smart Visual Analytics of Unconventional Data
- Social Computational Analytics for Trend Discovery and Social Media Marketing
- Twittener: Twitter speech synthesis with natural language processing
- Y Ma, H Peng, E Cambria. (2018). Targeted aspect-based sentiment analysis via embedding commonsense knowledge into an attentive LSTM. AAAI (pp. 5876-5883).
- E Cambria, S Poria, D Hazarika, K Kwok. (2018). SenticNet 5: Discovering conceptual primitives for sentiment analysis by means of context embeddings. AAAI (pp. 1795-1802).
- T Young, E Cambria, I Chaturvedi, H Zhou, S Biswas, M Huang. (2018). Augmenting end-to-end dialogue systems with commonsense knowledge. AAAI (pp. 4970-4977).
- E Cambria, S Poria, A Gelbukh, M Thelwall. (2017). Sentiment analysis is a big suitcase. IEEE Intelligent Systems, 32(6), 74-80.
- Cambria E, Hussain A. (2015). Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis. Springer, ISBN: 978-3-319-23654-4.
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